Beyond safety drivers: Applying air traffic control principles to support the deployment of driverless vehicles

PLoS One. 2020 May 21;15(5):e0232837. doi: 10.1371/journal.pone.0232837. eCollection 2020.

Abstract

By adopting and extending lessons from the air traffic control system, we argue that a nationwide remote monitoring system for driverless vehicles could increase safety dramatically, speed these vehicles' deployment, and provide employment. It is becoming clear that fully driverless vehicles will not be able to handle "edge" cases in the near future, suggesting that new methods are needed to monitor remotely driverless vehicles' safe deployment. While the remote operations concept is not new, a super-human driver is needed to handle sudden, critical events. We envision that the remote operators do not directly drive the vehicles, but provide input on high level tasks such as path-planning, object detection and classification. This can be achieved via input from multiple individuals, coordinated around a task at a moment's notice. Assuming a 10% penetration rate of driverless vehicles, we show that one remote driver can replace 14,840 human drivers. A comprehensive nationwide interoperability standard and procedure should be established for the remote monitoring and operation of driverless vehicles. The resulting system has potential to be an order of magnitude safer than today's ground transportation system. We articulate a research and policy roadmap to launch this nationwide system. Additionally, this hybrid human-AI system introduces a new job category, likely a source of employment nationwide.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms
  • Artificial Intelligence
  • Automation
  • Automobile Driving* / statistics & numerical data
  • Aviation / methods*
  • Computer Systems
  • Humans
  • Man-Machine Systems
  • Models, Theoretical
  • Motor Vehicles*
  • Robotics / methods*
  • Robotics / organization & administration
  • Robotics / statistics & numerical data
  • Robotics / trends
  • Safety
  • Software
  • United States

Grants and funding

This work is sponsored by the U.S. Department of Transportation Center for Connected and Automated Vehicles (CCAT), based at the University of Michigan’s Transportation Research Institute.